文章基本信息

标题：Improving The Steady State error and Convergence based on Variable Step Size Constant Modulus Blind Equalization Algorithm
本地全文：下载
作者：Raja Uyyala ; P. Satyanarayana
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2014
卷号：14
期号：10
页码：107-110
出版社：International Journal of Computer Science and Network Security
摘要：In this paper presents improving the steady state error and convergence based on variable step size modulation (VSS-CMA) blind equalization algorithm. In the past, constant-modulus algorithm (CMA) has low convergence rate and high error rate. In CMA has less step size can decrease the convergence rate, but at the same time it decrease the steady-state error. This paper propose a new variable step size constant-modulus algorithm (new VSS-CMA) with an adjustable step size that greatly increases the convergence rate for noise colorings with large eigenvalue spreads. A new VSS-CMA is simpler in computational requirements, faster convergence and lower steady state error and compare to conventional CMA, and VSS-CMA. The experimental results shows that the proposed VSS-CMA algorithm has considerably better performance than the conventional CMA and VSS-CMA
关键词：Cross correlation; VSS-CMA; blind equalization; adaptive blind training